GxE interaction effects of HCRTR2 single nucleotide polymorphism and adverse childhood experiences on methamphetamine use disorder.

Background: Methamphetamine use disorder (MUD) is a worldwide health concern. The hypothalamic orexin system regulates stress response and addictive behaviors. The genetic variation in the hypocretin receptor 2 (HCRTR2), rs2653349, is associated with substance use disorder.Objectives: We explored the gene-environment (GxE) interaction of rs2653349 and adverse childhood experiences (ACEs) associated with MUD susceptibility.Methods: Four hundred and one individuals (336 males, 65 females) with MUD and 348 healthy controls (288 males, 60 females) completed a self-report questionnaire evaluating ACEs, encompassing childhood abuse and household dysfunction categories, and were genotyped for SNP rs2653349. Methamphetamine use variables were collected using the Diagnostic Interview for Genetic Studies. We used regression analyses to assess the GxE effect on MUD risk.Results: The MUD group had a comparable genotypic distribution for rs2653349 to the control group, albeit with a higher prevalence and number of types of ACEs, correlating with an increased MUD risk (p < .05). No significant genetic impact of rs2653349 on MUD risk was found. However, we observed a GxE interaction effect between the minor allele of rs2653349 and the number of childhood abuse or household dysfunction types, correlating with a reduced MUD risk (OR = -0.71, p = .04, Benjamini-Hochberg adjusted p = .08 and OR = -0.59, p = .045, Benjamini-Hochberg adjusted p = .09, respectively).Conclusion: HCRTR2 SNP rs2653349 has no significant impact on MUD risk, but ACEs may increase this risk. GxE results suggest that rs2653349 could offer protection against developing MUD in individuals experiencing multiple types of ACEs.

Integrative pathway and network analysis provide insights on flooding-tolerance genes in soybean.

Soybean is highly sensitive to flooding and extreme rainfall. The phenotypic variation of flooding tolerance is a complex quantitative trait controlled by many genes and their interaction with environmental factors. We previously constructed a gene-pool relevant to soybean flooding-tolerant responses from integrated multiple omics and non-omics databases, and selected 144 prioritized flooding tolerance genes (FTgenes). In this study, we proposed a comprehensive framework at the systems level, using competitive (hypergeometric test) and self-contained (sum-statistic, sum-square-statistic) pathway-based approaches to identify biologically enriched pathways through evaluating the joint effects of the FTgenes within annotated pathways. These FTgenes were significantly enriched in 36 pathways in the Gene Ontology database. These pathways were related to plant hormones, defense-related, primary metabolic process, and system development pathways, which plays key roles in soybean flooding-induced responses. We further identified nine key FTgenes from important subnetworks extracted from several gene networks of enriched pathways. The nine key FTgenes were significantly expressed in soybean root under flooding stress in a qRT-PCR analysis. We demonstrated that this systems biology framework is promising to uncover important key genes underlying the molecular mechanisms of flooding-tolerant responses in soybean. This result supplied a good foundation for gene function analysis in further work.

Cytokine- and Vascular Endothelial Growth Factor-Related Gene-Based Genome-Wide Association Study of Low-Dose Ketamine Infusion in Patients with Treatment-Resistant Depression.

BACKGROUND AND OBJECTIVE: Ketamine may work as an anti-inflammatory agent, and it increases the levels of vascular endothelial growth factor (VEGF) in patients with treatment-resistant depression. However, whether genes related to pro-inflammatory and anti-inflammatory cytokines and VEGF may predict the treatment response to ketamine remains unknown.Therefore the aim of this study was to analyze whether specific genes related to inflammatory processes and VEGF were associated with treatment response to low-dose ketamine in patients with treatment-resistant depression. METHODS: Based on the genome data from our clinical trial, this study was a secondary analysis of candidate genes correlated with different timepoints of depressive symptoms. In total, 65 patients with treatment-resistant depression (n = 21 for ketamine 0.5 mg/kg, 20 for ketamine 0.2 mg/kg, and 24 for normal saline) were genotyped for 684,616 single nucleotide polymorphisms. Genes associated with 80 cytokines (i.e., interleukin [IL]-1, IL-6, tumor necrosis factor-α, and adiponectin) and VEGF (i.e., VEGF and VEGF receptors) were selected for the gene-based genome-wide association study on the antidepressant effect of a ketamine infusion. RESULTS: Specific single nucleotide polymorphisms, including rs2540315 and rs75746675 in IL1R1 and rs79568085 in VEGFC, were related to the rapid (within 240 min) antidepressant effect of a ketamine infusion; specific single nucleotide polymorphisms, such as Affx-20131665 in PIGF and rs8179353, rs8179353, and rs8179353 in TNFRSF8, were associated with the sustained (up to 2 weeks) antidepressant effect of low-dose (combined 0.5 mg/kg and 0.2 mg/kg) ketamine. CONCLUSIONS: Our findings further revealed that genes related to both anti-inflammatory and pro-inflammatory cytokines (i.e., IL-1, IL-2, IL-6, tumor necrosis factor-α, C-reactive protein, and adiponectin) and VEGF-FLK signaling predicted the treatment response to a ketamine infusion in patients with treatment-resistant depression. The synergic modulation of inflammatory and VEGF systems may contribute to the antidepressant effect of ketamine. CLINICAL TRIAL REGISTRATION: University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) number: UMIN000016985.

An advanced systems biology framework of feature engineering for cold tolerance genes discovery from integrated omics and non-omics data in soybean.

Soybean is sensitive to low temperatures during the crop growing season. An urgent demand for breeding cold-tolerant cultivars to alleviate the production loss is apparent to cope with this scenario. Cold-tolerant trait is a complex and quantitative trait controlled by multiple genes, environmental factors, and their interaction. In this study, we proposed an advanced systems biology framework of feature engineering for the discovery of cold tolerance genes (CTgenes) from integrated omics and non-omics (OnO) data in soybean. An integrative pipeline was introduced for feature selection and feature extraction from different layers in the integrated OnO data using data ensemble methods and the non-parameter random forest prioritization to minimize uncertainties and false positives for accuracy improvement of results. In total, 44, 143, and 45 CTgenes were identified in short-, mid-, and long-term cold treatment, respectively, from the corresponding gene-pool. These CTgenes outperformed the remaining genes, the random genes, and the other candidate genes identified by other approaches in an independent RNA-seq database. Furthermore, we applied pathway enrichment and crosstalk network analyses to uncover relevant physiological pathways with the discovery of underlying cold tolerance in hormone- and defense-related modules. Our CTgenes were validated by using 55 SNP genotype data of 56 soybean samples in cold tolerance experiments. This suggests that the CTgenes identified from our proposed systematic framework can effectively distinguish cold-resistant and cold-sensitive lines. It is an important advancement in the soybean cold-stress response. The proposed pipelines provide an alternative solution to biomarker discovery, module discovery, and sample classification underlying a particular trait in plants in a robust and efficient way.

A multiple phenotype imputation method for genetic diversity and core collection in Taiwanese vegetable soybean.

Establishment of vegetable soybean (edamame) [Glycine max (L.) Merr.] germplasms has been highly valued in Asia and the United States owing to the increasing market demand for edamame. The idea of core collection (CC) is to shorten the breeding program so as to improve the availability of germplasm resources. However, multidimensional phenotypes typically are highly correlated and have different levels of missing rate, often failing to capture the underlying pattern of germplasms and select CC precisely. These are commonly observed on correlated samples. To overcome such scenario, we introduced the "multiple imputation" (MI) method to iteratively impute missing phenotypes for 46 morphological traits and jointly analyzed high-dimensional imputed missing phenotypes (EC impu ) to explore population structure and relatedness among 200 Taiwanese vegetable soybean accessions. An advanced maximization strategy with a heuristic algorithm and PowerCore was used to evaluate the morphological diversity among the EC impu . In total, 36 accessions (denoted as CC impu ) were efficiently selected representing high diversity and the entire coverage of the EC impu . Only 4 (8.7%) traits showed slightly significant differences between the CC impu and EC impu . Compared to the EC impu , 96% traits retained all characteristics or had a slight diversity loss in the CC impu . The CC impu exhibited a small percentage of significant mean difference (4.51%), and large coincidence rate (98.1%), variable rate (138.76%), and coverage (close to 100%), indicating the representativeness of the EC impu . We noted that the CC impu outperformed the CC raw in evaluation properties, suggesting that the multiple phenotype imputation method has the potential to deal with missing phenotypes in correlated samples efficiently and reliably without re-phenotyping accessions. Our results illustrated a significant role of imputed missing phenotypes in support of the MI-based framework for plant-breeding programs.

Genetic Pathways and Functional Subnetworks for the Complex Nature of Bipolar Disorder in Genome-Wide Association Study.

Bipolar disorder is a complex psychiatric trait that is also recognized as a high substantial heritability from a worldwide distribution. The success in identifying susceptibility loci for bipolar disorder (BPD) has been limited due to its complex genetic architecture. Growing evidence from association studies including genome-wide association (GWA) studies points to the need of improved analytic strategies to pinpoint the missing heritability for BPD. More importantly, many studies indicate that BPD has a strong association with dementia. We conducted advanced pathway analytics strategies to investigate synergistic effects of multilocus within biologically functional pathways, and further demonstrated functional effects among proteins in subnetworks to examine mechanisms underlying the complex nature of bipolarity using a GWA dataset for BPD. We allowed bipolar susceptible loci to play a role that takes larger weights in pathway-based analytic approaches. Having significantly informative genes identified from enriched pathways, we further built function-specific subnetworks of protein interactions using MetaCore. The gene-wise scores (i.e., minimum p-value) were corrected for the gene-length, and the results were corrected for multiple tests using Benjamini and Hochberg's method. We found 87 enriched pathways that are significant for BPD; of which 36 pathways were reported. Most of them are involved with several metabolic processes, neural systems, immune system, molecular transport, cellular communication, and signal transduction. Three significant and function-related subnetworks with multiple hotspots were reported to link with several Gene Ontology processes for BPD. Our comprehensive pathway-network frameworks demonstrated that the use of prior knowledge is promising to facilitate our understanding between complex psychiatric disorders (e.g., BPD) and dementia for the access to the connection and clinical implications, along with the development and progression of dementia.

Treatment response to low-dose ketamine infusion for treatment-resistant depression: A gene-based genome-wide association study.

BACKGROUNDS: Evidence suggested the crucial roles of brain-derived neurotrophic factor (BDNF) and glutamate system functioning in the antidepressant mechanisms of low-dose ketamine infusion in treatment-resistant depression (TRD). METHODS: 65 patients with TRD were genotyped for 684,616 single nucleotide polymorphisms (SNPs). Twelve ketamine-related genes were selected for the gene-based genome-wide association study on the antidepressant effect of ketamine infusion and the resulting serum ketamine and norketamine levels. RESULTS: Specific SNPs and whole genes involved in BDNF-TrkB signaling (i.e., rs2049048 in BDNF and rs10217777 in NTRK2) and the glutamatergic and GABAergic systems (i.e., rs16966731 in GRIN2A) were associated with the rapid (within 240 min) and persistent (up to 2 weeks) antidepressant effect of low-dose ketamine infusion and with serum ketamine and norketamine levels. DISCUSSION: Our findings confirmed the predictive roles of BDNF-TrkB signaling and glutamatergic and GABAergic systems in the underlying mechanisms of low-dose ketamine infusion for TRD treatment.

Differences in serum orexin-A levels between the acute and subacute withdrawal phases in individuals who use methamphetamine.

Orexin has been suggested to play a role in regulating the reward circuits and enhancing drug-seeking behaviors; however, its role in methamphetamine (METH) addiction remains unclear. We previously found that blood orexin-A levels are upregulated in individuals with recent METH exposure. Whether the levels would be altered following withdrawal is unknown. In this study, we compared the levels of serum orexin-A in individuals who use METH between the acute withdrawal (AW) phase and the subacute withdrawal (SAW) phase at baseline (T1) and examined the alterations in these levels after 2 weeks of abstinence (T2). In total, 60 participants (51 men and 9 women) were enrolled in the study; 20 participants with METH-positive urine test results were included in the AW group, and 40 participants with METH-negative urine test results who had self-reportedly last taken METH within the preceding 1-2 months were included in the SAW group. Serum orexin-A levels were measured using enzyme-linked immunosorbent assay. No significant differences in orexin-A levels were observed between the AW and SAW groups at baseline (p = .06). After 2 additional weeks of abstinence, the levels decreased significantly in the SAW group (0.58 ± 0.13 ng/mL) but not in the AW group (0.50 ± 0.14 ng/mL, p = .004). Our results demonstrated that orexin-A levels might decrease after a longer period of METH withdrawal, indicating that the orexin system is dysregulated in the addictive process of METH. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A Modified Roger's Distance Algorithm for Mixed Quantitative-Qualitative Phenotypes to Establish a Core Collection for Taiwanese Vegetable Soybeans.

Vegetable soybeans [Glycine max (L.) Merr.] have characteristics of larger seeds, less beany flavor, tender texture, and green-colored pods and seeds. Rich in nutrients, vegetable soybeans are conducive to preventing neurological disease. Due to the change of dietary habits and increasing health awareness, the demand for vegetable soybeans has increased. To conserve vegetable soybean germplasms in Taiwan, we built a core collection of vegetable soybeans, with minimum accessions, minimum redundancy, and maximum representation. Initially, a total of 213 vegetable soybean germplasms and 29 morphological traits were used to construct the core collection. After redundant accessions were removed, 200 accessions were retained as the entire collection, which was grouped into nine clusters. Here, we developed a modified Roger's distance for mixed quantitative-qualitative phenotypes to select 30 accessions (denoted as the core collection) that had a maximum pairwise genetic distance. No significant differences were observed in all phenotypic traits (p-values > 0.05) between the entire and the core collections, except plant height. Compared to the entire collection, we found that most traits retained diversities, but seven traits were slightly lost (ranged from 2 to 9%) in the core collection. The core collection demonstrated a small percentage of significant mean difference (3.45%) and a large coincidence rate (97.70%), indicating representativeness of the entire collection. Furthermore, large values in variable rate (149.80%) and coverage (92.5%) were in line with high diversity retained in the core collection. The results suggested that phenotype-based core collection can retain diversity and genetic variability of vegetable soybeans, providing a basis for further research and breeding programs.

Gene-Based Association Analysis Suggests Association of HTR2A With Antidepressant Treatment Response in Depressed Patients.

The serotonin [5-hydroxytryptamine (5-HT)] system has been implicated in the pathogenesis of major depressive disorder (MDD). Among the 5-HT receptor subtypes, 5-HT2 is one of the major pharmacological therapeutic targets for MDD. There have been inconsistent findings in previous pharmacogenetic studies investigating the antidepressant therapeutic response using one or several 5-HT2A (HTR2A) genetic polymorphisms. By using gene-based association analysis, we hope to identify genetic variants of HTR2A which are related to MDD susceptibility and its antidepressant therapeutic response. 288 HTR2A single nucleotide polymorphisms in MDD susceptibility have been investigated through a case-control (455 MDD patients and 2, 998 healthy controls) study, as well as in antidepressant efficacy (n = 455) in our current research. The 21-item Hamilton Rating Scale for Depression was used to evaluate measures of antidepressant therapeutic efficacy. From two MDD groups in the antidepressant therapeutic response, by using gene-based analyses, we have identified 14 polymorphisms as suggestive markers for therapeutic response (13 for remission and 1 for response) in both meta- and mega-analyses. All of these HTR2A reported polymorphisms did not reach statistical significance in the case-control association study. This current investigation supported the link between HTR2A variants and antidepressant therapeutic response in MDD but not with MDD susceptibility.

Prioritization and Evaluation of Flooding Tolerance Genes in Soybean [Glycine max (L.) Merr.].

Soybean [Glycine max (L.) Merr.] is one of the most important legume crops abundant in edible protein and oil in the world. In recent years there has been increasingly more drastic weather caused by climate change, with flooding, drought, and unevenly distributed rainfall gradually increasing in terms of the frequency and intensity worldwide. Severe flooding has caused extensive losses to soybean production and there is an urgent need to breed strong soybean seeds with high flooding tolerance. The present study demonstrates bioinformatics big data mining and integration, meta-analysis, gene mapping, gene prioritization, and systems biology for identifying prioritized genes of flooding tolerance in soybean. A total of 83 flooding tolerance genes (FTgenes), according to the appropriate cut-off point, were prioritized from 36,705 test genes collected from multidimensional genomic features linking to soybean flooding tolerance. Several validation results using independent samples from SoyNet, genome-wide association study, SoyBase, GO database, and transcriptome databases all exhibited excellent agreement, suggesting these 83 FTgenes were significantly superior to others. These results provide valuable information and contribution to research on the varieties selection of soybean.

Orexin-A Levels in Relation to the Risk of Metabolic Syndrome in Patients with Schizophrenia Taking Antipsychotics.

Background: The role of orexin-A in regulating metabolic homeostasis has been recognized, but its association with antipsychotic-induced metabolic abnormalities remains unclear. We investigated the association between orexin-A levels and metabolic syndrome in patients with schizophrenia treated with clozapine or less obesogenic antipsychotics compared with nonpsychiatric controls. Methods: Plasma orexin-A levels and metabolic parameters were determined in 159 patients with schizophrenia: 109 taking clozapine; 50 taking aripiprazole, amisulpride, ziprasidone, or haloperidol; and 60 nonpsychiatric controls. Results: Orexin-A levels were significantly higher in the group taking less obesogenic antipsychotics, followed by the clozapine group and the controls (F=104.6, P<.01). Higher orexin-A levels were correlated with better metabolic profiles in the patient groups but not in the controls. Regression analyses revealed that the patients with higher orexin-A levels had significantly lower risk of metabolic syndrome (adjusted odds ratio [OR]=0.04, 95% CI: 0.01-0.38 for the 2nd tertile; OR=0.04, 95% CI: 0.01-0.36 for the 3rd tertile, compared with the first tertile), after adjustment for age, sex, smoking history, types of antipsychotics (clozapine vs less obesogenic antipsychotics), duration of antipsychotic treatment, and disease severity. Conclusions: Our results revealed that the orexin-A level was upregulated in patients with schizophrenia treated with antipsychotics, especially for the group taking less obesogenic antipsychotics. Furthermore, higher orexin-A levels were independently associated with better metabolic profiles. These observations suggest that an upregulation of orexin-A has a protective effect against the development of metabolic abnormalities in patients with schizophrenia receiving antipsychotic treatment.

Gene-based analysis of genes related to neurotrophic pathway suggests association of BDNF and VEGFA with antidepressant treatment-response in depressed patients.

It is well established that brain-derived neurotrophic factor (BDNF) signaling pathway plays a key role in the pathophysiology of major depressive disorder (MDD) and in therapeutic mechanisms of antidepressants. We aim to identify genetic vairiants related to MDD susceptibility and antidepressant therapeutic response by using gene-based association analysis with genes related to the neurotrophic pathway. The present study investigated the role of genetic variants in the 10 neurotrophic-related genes (BDNF, NGFR, NTRK2, MTOR, VEGFA, S100A10, SERPINE1, ARHGAP33, GSK3B, CREB1) in MDD susceptibility through a case-control (455 MDD patients and 2,998 healthy controls) study and in antidepressant efficacy (n = 455). Measures of antidepressant therapeutic efficacy were evaluated using the 21-item Hamilton Rating Scale for Depression. Our single-marker and gene-based analyses with ten genes related to the neurotrophic pathway identified 6 polymorphisms that reached a significant level (p-value < 5.0 × 10-3) in both meta- and mega-analyses in antidepressant therapeutic response. One polymorphism was mapped to BDNF and 5 other polymorphisms were mapped to VEGFA. For case-control association study, we found that all of these reported polymorphisms and genes did not reach a suggestive level. The present study supported a role of BDNF and VEGFA variants in MDD therapeutic response.

No association of CYP2E1 genetic polymorphisms with alcohol dependence in Han Taiwanese population.

Cytochrome P450 2E1 (CYP2E1) gene is one of the candidate genes for alcohol dependence (AD). Four single nucleotide polymorphisms (SNPs) of CYP2E1 gene (CYP2E1*1D, *5B, *6 and *1B) have been associated with AD previously in other ethnic populations. To date, only CYP2E1*5B and *6 SNPs have been investigated in relation to AD in our population. The objective of the study was to examine the genetic associations of CYP2E1 covering the four above-noted SNPs conjointly with AD in Han Taiwanese population based on single SNP analysis and haplotype-based approach. We enrolled a total of 340 patients fulfilling DSM-IV-TR diagnostic criteria of AD and 319 healthy controls and genotyped them for the above four SNPs of CYP2E1 gene. By comparing the differences of genotype, allele, and pertinent haplotype frequencies, we did not support a genetic association between CYP2E1 and AD in Han Taiwanese either by single allele tests or haplotype-based analyses.

Effects of circadian clock genes and environmental factors on cognitive aging in old adults in a Taiwanese population.

Previous animal studies have indicated associations between circadian clock genes and cognitive impairment . In this study, we assessed whether 11 circadian clockgenes are associated with cognitive aging independently and/or through complex interactions in an old Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing cognitive aging. A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examinations (MMSE) were administered to all subjects, and MMSE scores were used to evaluate cognitive function. Our data showed associations between cognitive aging and single nucleotide polymorphisms (SNPs) in 4 key circadian clock genes, CLOCK rs3749473 (p = 0.0017), NPAS2 rs17655330 (p = 0.0013), RORA rs13329238 (p = 0.0009), and RORB rs10781247 (p = 7.9 x 10-5). We also found that interactions between CLOCK rs3749473, NPAS2 rs17655330, RORA rs13329238, and RORB rs10781247 affected cognitive aging (p = 0.007). Finally, we investigated the influence of interactions between CLOCK rs3749473, RORA rs13329238, and RORB rs10781247 with environmental factors such as alcohol consumption, smoking status, physical activity, and social support on cognitive aging (p = 0.002 ~ 0.01). Our study indicates that circadian clock genes such as the CLOCK, NPAS2, RORA, and RORB genes may contribute to the risk of cognitive aging independently as well as through gene-gene and gene-environment interactions.

Effects of circadian clock genes and health-related behavior on metabolic syndrome in a Taiwanese population: Evidence from association and interaction analysis.

Increased risk of developing metabolic syndrome (MetS) has been associated with the circadian clock genes. In this study, we assessed whether 29 circadian clock-related genes (including ADCYAP1, ARNTL, ARNTL2, BHLHE40, CLOCK, CRY1, CRY2, CSNK1D, CSNK1E, GSK3B, HCRTR2, KLF10, NFIL3, NPAS2, NR1D1, NR1D2, PER1, PER2, PER3, REV1, RORA, RORB, RORC, SENP3, SERPINE1, TIMELESS, TIPIN, VIP, and VIPR2) are associated with MetS and its individual components independently and/or through complex interactions in a Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing MetS and its individual components. A total of 3,000 Taiwanese subjects from the Taiwan Biobank were assessed in this study. Metabolic traits such as waist circumference, triglyceride, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, and fasting glucose were measured. Our data showed a nominal association of MetS with several single nucleotide polymorphisms (SNPs) in five key circadian clock genes including ARNTL, GSK3B, PER3, RORA, and RORB; but none of these SNPs persisted significantly after performing Bonferroni correction. Moreover, we identified the effect of GSK3B rs2199503 on high fasting glucose (P = 0.0002). Additionally, we found interactions among the ARNTL rs10832020, GSK3B rs2199503, PER3 rs10746473, RORA rs8034880, and RORB rs972902 SNPs influenced MetS (P < 0.001 ~ P = 0.002). Finally, we investigated the influence of interactions between ARNTL rs10832020, GSK3B rs2199503, PER3 rs10746473, and RORB rs972902 with environmental factors such as alcohol consumption, smoking status, and physical activity on MetS and its individual components (P < 0.001 ~ P = 0.002). Our study indicates that circadian clock genes such as ARNTL, GSK3B, PER3, RORA, and RORB genes may contribute to the risk of MetS independently as well as through gene-gene and gene-environment interactions.

The ADAMTS9 gene is associated with cognitive aging in the elderly in a Taiwanese population.

Evidence indicates that the pathophysiologic mechanisms associated with insulin resistance may contribute to cognitive aging and Alzheimer's diseases. In this study, we hypothesize that single nucleotide polymorphisms (SNPs) within insulin resistance-associated genes, such as the ADAM metallopeptidase with thrombospondin type 1 motif 9 (ADAMTS9), glucokinase regulator (GCKR), and peroxisome proliferator activated receptor gamma (PPARG) genes, may be linked with cognitive aging independently and/or through complex interactions in an older Taiwanese population. A total of 547 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examinations (MMSE) were administered to all subjects, and MMSE scores were used to measure cognitive functions. Our data showed that four SNPs (rs73832338, rs9985304, rs4317088, and rs9831846) in the ADAMTS9 gene were significantly associated with cognitive aging among the subjects (P = 1.5 x 10-6 ~ 0.0002). This association remained significant after performing Bonferroni correction. Additionally, we found that interactions between the ADAMTS9 rs9985304 and ADAMTS9 rs76346246 SNPs influenced cognitive aging (P < 0.001). However, variants in the GCKR and PPARG genes had no association with cognitive aging in our study. Our study indicates that the ADAMTS9 gene may contribute to susceptibility to cognitive aging independently as well as through SNP-SNP interactions.

The rs1277306 Variant of the REST Gene Confers Susceptibility to Cognitive Aging in an Elderly Taiwanese Population.

BACKGROUND/AIMS: There is growing evidence that the RE1-silencing transcription factor (REST) gene may contribute to cognitive aging and Alzheimer diseases. In this replication study, we reassessed whether single nucleotide polymorphisms (SNPs) within the REST gene are linked with cognitive aging independently and/or through complex interactions in an older Taiwanese population. METHODS: A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examination (MMSE) scores were performed for all subjects to weigh cognitive functions. RESULTS: Our data showed that the REST rs1277306 SNP was significantly associated with cognitive aging among all subjects (p = 0.0052). Furthermore, the association remained significant for individuals without APOE ε4 allele (p = 0.0092), but not for individuals with at least 1 APOE ε4 allele. This association remained significant after Bonferroni correction. Additionally, we found the interactions between the rs1713985 and rs1277306 SNPs on cognitive aging (p = 0.016). However, the 3-marker haplotype derived from the rs1713985, rs3796529, and rs7680734 SNPs in the REST gene demonstrated no association with cognitive aging. CONCLUSION: Our study indicates that the REST gene may contribute to susceptibility to cognitive aging independently as well as through SNP-SNP and APOE-REST interactions.